Bank Note Detection Using Deep Learning Techniques

dc.contributor.authorRoy, Sojib
dc.contributor.authorSatu, Kh. Munsura Akter
dc.date.accessioned2023-05-03T04:46:23Z
dc.date.available2023-05-03T04:46:23Z
dc.date.issued23-02-18
dc.description.abstractThis report presents a Bangladeshi Banknote detection system using a Deep Convolutional Neural Network. This project is usually designed for people who do not recognize or cannot see the Bangladeshi banknotes. Visually impaired humans face trouble in figuring out and spotting the unique types of banknotes due to a few reasons. Many projects like this have been followed before this project was completed. Some of the works of others are also mentioned in this paper. The detection system is also capable of identifying the Bangladeshi Banknotes that are rumpled, decrepit, or may be worn. The detection system consists of image preprocessing, image evaluation, and image recognition. In this project, 3000 images have been used. There are 50 taka, 100 taka, 200 taka, 500 taka, 1000 taka. This project has been completed using CNN, Vgg16, Transfer learning, and transfer learning-based improved CNN model. We get Better accuracy from improve CNN. We get medium accuracy form Deep CNN and we get low accuracy from VGG16 and transfer learning.
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/10293
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/10293
dc.language.isoen_US
dc.publisherDaffodil International University
dc.sourceDIU Institutional Repository
dc.subjectNeural networks
dc.subjectDetection system
dc.titleBank Note Detection Using Deep Learning Techniques
dc.typeOther

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